> ## Documentation Index > Fetch the complete documentation index at: https://docs.vortexiq.ai/llms.txt > Use this file to discover all available pages before exploring further. # When Did Speed Get Worse?, Website Performance (PageSpeed + CrUX) **Metrics type:** [Card](/nerve-centre/overview#metrics-types-explained) ## At a glance > **Composite regression timeline across all CWV trends**, surfaces the dates of significant CWV regressions across the LCP / INP / CLS / TTFB / FCP trends in a single chronological view. **The "what changed when" diagnostic surface**: instead of reading 5 separate trend cards, this card shows every regression event ranked by severity and decorated with the affected metric. **Critical for incident-response retrospective**: when leadership asks "why did our pass rate drop?", this card produces the answer in one screen. | | | | --------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **What it counts** | Chronological timeline of regression events detected across all CWV trends. Each event includes: date, affected metric (LCP / INP / CLS / TTFB / FCP / score / pass rate), magnitude (delta), severity classification, and inferred cause when correlatable with deploy / content events. | | **Sample type** | **Field data** for CrUX-derived metrics; **lab data** for score-derived events. The composite uses both data sources to surface a unified timeline. | | **Detection criteria** | A regression event is recorded when: (a) **field metric** moves > +2x typical run-to-run variance over a 7-day rolling window; (b) **lab metric** moves > 5 points / 200ms / 0.05 within a single audit; (c) **threshold crossing**: the metric crosses a Google-defined band boundary (e.g. CWV pass rate from above to below 75 percent). | | **Severity classification** | **Critical**: threshold crossing (passing → failing band). **High**: regression > 30 percent of band width without crossing threshold. **Medium**: regression > 15 percent without crossing. **Low**: persistent drift beyond noise but small in magnitude. | | **Inference of cause** | When deploy log or CMS audit log is available, the timeline cross-references regression dates with shipped changes. **High-confidence inferences** (deploy on the same day, single-metric pattern matching the change-type): annotated as "likely cause: X". **Lower-confidence**: surfaces candidate events without claiming attribution. | | **Why this card matters** | The trio of TTFB + FCP + LCP trends already reveals regression class (server vs render-blocking vs LCP-element). This card aggregates the trio + INP + CLS trends + score trend + pass rate trend into a unified timeline. **Saves 10-15 minutes of cross-card cross-referencing** per incident-response investigation. | | **The "leadership read" framing** | When leadership asks "why is our CWV failing?", the card produces a 2-3 line answer: "Three regressions in the last 6 months: Feb 26 hero carousel deploy (+460ms LCP), Mar 26 marketing-stack expansion (+660ms LCP, +60ms INP), Apr 26 BFCM imagery (+580ms LCP, +0.02 CLS). Recovery requires reversing each contribution; estimated 6-week cycle." | | **Currency** | n/a, timeline view. | | **Time window** | `T-180D` rolling timeline (default 6-month look-back). | | **Alert trigger** | New critical-severity event detected (threshold crossing). | | **Sentiment key** | `null` (composite view). | | **Roles** | owner, operations | ## Calculation Calculated automatically from your Website Performance (PageSpeed + CrUX) data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading. ## Worked example A UK-based BigCommerce fashion store, regression timeline over 6 months ending Wednesday 15 May 26. | Date | Severity | Affected metrics | Magnitude | Inferred cause | | --------------- | ------------ | --------------------- | ---------------------------- | --------------------------------------------------------------- | | 14 Jan 26 | High | LCP, FCP | LCP +260ms, FCP +280ms | Klaviyo popup CSS landed as render-blocking external stylesheet | | 03 Feb 26 | **Critical** | Pass rate (84% → 78%) | -6pp pass rate; LCP +460ms | Hero carousel deploy (heavier images, 4 PNGs at 2.8MB) | | 17 Feb 26 | **Critical** | Pass rate (78% → 72%) | Threshold crossing below 75% | Compounded with Klaviyo popup, pushed below threshold | | 12 Mar 26 | Critical | TTFB, score | TTFB +260ms, score -8 | BFCM-prep dynamic-pricing widget disabled CDN caching | | 18 Mar 26 | High | INP | INP +60ms | Klaviyo SDK update added behavior tracking | | 25 Mar 26 | High | INP | INP +80ms | Filter widget refactor introduced long tasks | | 09 Apr 26 | High | LCP | LCP +580ms | BFCM hero campaign images uploaded unoptimised | | 22 Apr 26 | Medium | INP | INP +40ms | Hotjar session recording added | | **Most recent** | **Failing** | **All composite** | **64.8% pass rate** | **Sustained sub-75% for 3 months** | What the timeline is telling us: 1. **Eight distinct regression events identified** over the 6-month window, with two critical-severity threshold crossings (Feb 03 and Feb 17). The cumulative effect is the current 64.8% pass rate. 2. **Two critical events were missable in real-time** because each individual event seemed minor. Feb 03 was a single hero deploy; Feb 17 was a "stabilisation" of the previous deploy. The threshold crossing happened because cumulative effect crossed 75%, not because any single deploy was catastrophic. 3. **The Mar 12 critical TTFB regression** had a different shape. Single dominant cause (cache config change), single dominant metric (TTFB), single dominant severity (critical). **Easier to attribute and easier to fix** than the cumulative-drift pattern. 4. **Clear leadership story**: "We had 8 regression events over 6 months; 3 critical, 4 high, 1 medium. Two threshold crossings put us in CWV failing band. The dominant causes were image-related (hero carousel, BFCM imagery) and cache-related (BFCM dynamic-pricing widget). Recovery requires reversing the image and cache changes, estimated 6-week cycle, expected to cross back above 75% threshold by week 4-5." 5. **Recovery prioritisation by impact × ease-of-fix**: * **Mar 12 cache config**: highest leverage, easy fix (config rollback). Tackle first. * **Apr 09 BFCM imagery**: high leverage, mechanical fix (image format conversion). Tackle second. * **Feb 03 hero carousel**: high leverage, requires re-export workflow. Tackle third. * **Jan 14 Klaviyo CSS**: medium leverage, easy fix (defer). Tackle in parallel with above. * **Mar 18, Mar 25, Apr 22 INP events**: medium leverage, more invasive (refactor). Tackle in week 3-4. 6. **Defence going forward**: enable critical-severity alerts (threshold crossings) + high-severity alerts (>30% band-width regression). The timeline becomes a continuous monitoring surface rather than a retrospective tool. The diagnostic flow: 1. **Read top-3 by severity.** Critical events first, then high, then medium. 2. **Cross-reference deploy / content / vendor logs** for each event date. 3. **Plan recovery sequence by impact × ease-of-fix.** 4. **Re-enable alerts** for ongoing monitoring. Rapid-response playbook: | Time horizon | Action | | -------------- | --------------------------------------------------------- | | First 1 hour | Identify critical-severity events; understand each cause. | | First week | Begin recovery on highest-leverage easiest-fix events. | | First month | Field metrics begin reflecting cumulative recovery. | | Quarter onward | Continuous monitoring via alerts. | ## Sibling cards merchants should reference together | Card | Why merchants reach for it | | ---------------------------------------------------------------------------------------------------- | ----------------------------------------- | | [`crux_lcp_trend`](/nerve-centre/kpi-cards/website-performance/load-speed-over-time) | LCP-specific trend; this card aggregates. | | [`crux_inp_trend`](/nerve-centre/kpi-cards/website-performance/responsiveness-over-time) | INP-specific trend. | | [`crux_cls_trend`](/nerve-centre/kpi-cards/website-performance/layout-stability-over-time) | CLS-specific trend. | | [`crux_ttfb_trend`](/nerve-centre/kpi-cards/website-performance/server-speed-over-time) | TTFB-specific trend. | | [`crux_fcp_trend`](/nerve-centre/kpi-cards/website-performance/first-content-over-time) | FCP-specific trend. | | [`crux_pass_rate_trend`](/nerve-centre/kpi-cards/website-performance/speed-test-pass-rate-over-time) | Composite pass rate trend. | | [`psi_score_trend`](/nerve-centre/kpi-cards/website-performance/performance-score-over-time) | Lab score trend. | | [`psi_biggest_regression`](/nerve-centre/kpi-cards/website-performance/biggest-regression) | Per-URL regression detection. | ## Reconciling against the vendor's own dashboard **Where to look:** This is a Vortex IQ-derived composite card; no direct external equivalent. The closest comparable view is reading GSC's CWV trend chart while cross-referencing your deploy log manually, that's exactly the work this card automates. **Why the timeline may include events external tools wouldn't see:** | Reason | What it means | | -------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------- | | **Sub-threshold but persistent regressions.** Smaller deltas that don't trigger a single-trend alert but accumulate. | The composite catches drift; single-trend alerts catch step changes. | | **Cross-metric correlation.** TTFB regression on date X plus FCP regression on date X = single root-cause event. | Surfaces unified incidents that single-trend views fragment. | **Cross-connector reconciliation:** primarily internal (aggregates all sub-trend cards). **Quick rule for support tickets:** if a merchant says *"Vortex IQ shows a critical event but GSC doesn't flag it"*, the most common cause is GSC's threshold being more lenient than the composite's regression-detection threshold. **Vortex IQ surfaces drift earlier**; GSC reflects ranking-impact events later. ## Known limitations / merchant FAQs **Why does this card label some events as "high-confidence cause" and others as "candidate cause"?** When deploy logs and CMS audit logs are integrated, the timeline matches regression dates with shipped changes. **High-confidence**: same-day deploy + matching change-type pattern (e.g. CSS deploy + FCP regression). **Candidate**: multiple shipped changes on the same day, can't disambiguate. **No inference**: regression date doesn't match any logged change. **My timeline shows 8 events but I only remember 3 deploys. Why?** Some regressions trace to non-deploy events: vendor-side updates (Klaviyo, Tidio pushed new versions without merchant action), content uploads (marketing replaced hero images via CMS), or infrastructure changes (CDN config drift). **The timeline catches all regression events**, including the ones the merchant didn't directly cause. **How far back does the timeline go?** Default 6-month look-back. Extends to 12 months for deeper investigation if configured. Beyond 12 months, CrUX historical data quality degrades for some metrics and the timeline becomes less useful. **Should I act on every event in the timeline?** Prioritise by severity × ease-of-fix. **Critical events** (threshold crossings) demand action; **medium and low events** are informational. The card surfaces all events; the recovery plan addresses only the most leverage-positive subset. **Can I export the timeline for retrospective post-mortems?** The Vortex IQ dashboard supports CSV export of the timeline. The Vortex Mind Pre-Launch Readiness report includes the timeline in its outputs. **Why is sustained drift sometimes flagged as critical?** When sustained drift compounds to push a metric across a band threshold (e.g. pass rate from 76% to 73%), the threshold crossing is critical regardless of whether any single event was large. **The card flags the crossing date** even when no single event would qualify on its own. *** ### Tracked live in Vortex IQ Nerve Centre *When Did Speed Get Worse?* is one of hundreds of KPI pulses Vortex IQ tracks across Website Performance (PageSpeed + CrUX) and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English. [Start for free](https://app.vortexiq.ai/login) or [book a demo](https://www.vortexiq.ai/contact-us) to see this metric running on your own data.